Actively Recruiting

Age: 18Years +
All Genders
Healthy Volunteers
ID06773832

Artificial Intelligence Predicts the Pathology and Endoscopic Classification of Colorectal Polyps During Colonoscopy

Led by Peking Union Medical College Hospital · Updated on 2025-01-14

400

Participants Needed

1

Research Sites

N/A

Total Duration

On this page

AI-Summary

What this Trial Is About

Researchers are evaluating the use of artificial intelligence (AI) to predict the pathology and endoscopic classification of colorectal polyps during colonoscopy. Colonoscopy with optical diagnosis based on polyp appearance can guide treatment choices, reduce unnecessary polypectomies, and help plan follow-up, which benefits patients and healthcare systems. However, current classification methods require extensive training and none can accurately diagnose all polyp types, limiting the widespread use of optical diagnosis. AI, specifically computer-aided diagnosis (CADx), has shown promise in identifying small polyps, but its effectiveness for larger polyps (5mm or more) and serrated lesions remains unclear.

CONDITIONS

Brief Title

AI in Predicting Polyp Pathology and Endoscopic Classification

Who Can Participate

Age: 18Years +
All Genders
Healthy Volunteers

Eligibility Criteria

Eligible

You may qualify if you...

  • Outpatients or inpatients undergoing routine colonoscopy screening at multicenter hospital endoscopy centers
  • Aged 18 years or older
  • Understand the study content and have signed the informed consent form
Not Eligible

You will not qualify if you...

  • Gastroparesis or gastric outlet obstruction
  • Known or suspected intestinal obstruction or perforation
  • Severe chronic renal failure (creatinine clearance less than 30 mL/minute)
  • Severe congestive heart failure (New York Heart Association Class III or IV)
  • Currently pregnant or breastfeeding
  • Toxic colitis or megacolon
  • Poorly controlled hypertension (systolic blood pressure greater than 180 mmHg and/or diastolic blood pressure greater than 100 mmHg)
  • Moderate or massive active gastrointestinal bleeding (more than 100 mL/day)
  • Significant psychiatric or psychological illness
  • Allergy to medications used for bowel preparation
  • Patients who have undergone colorectal surgery

AI-Screening

AI-Powered Screening

Complete this quick 3-step screening to check your eligibility

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3
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Your Study Journey

Screening

Duration - 2 to 4 weeks

Participants are screened for eligibility to participate in the trial.

1 visit (in-person)

Diagnostic Evaluation

Duration - Single day procedure

Participants undergo routine colonoscopy screening during which images of colorectal polyps are captured and analyzed by the AI model to predict pathology and endoscopic classification.

1 visit (in-person)

Long-term Monitoring

Duration - Up to 2 years

Participants are observed for up to 2 years to assess the accuracy and other parameters of the AI model in diagnosing colorectal polyps based on optical diagnosis and endoscopic classification.

Follow-up assessments as per routine care

Trial Site Locations

Total: 1 location

1

Peking Union Medical College Hospital

Beijing, China, 100730

Actively Recruiting

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Research Team

W

Wenmo Hu, MD

How is the study designed?

Study Type

OBSERVATIONAL

Masking

N/A

Allocation

N/A

Model

N/A

Primary Purpose

N/A

Number of Arms

1

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Frequently Asked Questions

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Published Research Related To This Trial

Optical diagnosis of colorectal polyp images using a newly developed computer-aided diagnosis system (CADx) compared with intuitive optical diagnosis.

Quirine E W van der Zander, Ramon M Schreuder, Roger Fonollà...

https://pubmed.ncbi.nlm.nih.gov/33368056

Narrow band imaging optical diagnosis of small colorectal polyps in routine clinical practice: the Detect Inspect Characterise Resect and Discard 2 (DISCARD 2) study.

Colin J Rees, Praveen T Rajasekhar, Ana Wilson...

https://pubmed.ncbi.nlm.nih.gov/27196576

Development and validation of the WASP classification system for optical diagnosis of adenomas, hyperplastic polyps and sessile serrated adenomas/polyps.

Joep E G IJspeert, Barbara A J Bastiaansen, Monique E van Leerdam...

https://pubmed.ncbi.nlm.nih.gov/25753029

Aim to unify the narrow band imaging (NBI) magnifying classification for colorectal tumors: current status in Japan from a summary of the consensus symposium in the 79th Annual Meeting of the Japan Gastroenterological Endoscopy Society.

Shinji Tanaka, Yasushi Sano

https://pubmed.ncbi.nlm.nih.gov/21535219

High-resolution chromoendoscopy for the diagnosis of diminutive colon polyps: implications for colon cancer screening.

A M Axelrad, D E Fleischer, A J Geller...

https://pubmed.ncbi.nlm.nih.gov/8613016

Cost savings in colonoscopy with artificial intelligence-aided polyp diagnosis: an add-on analysis of a clinical trial (with video).

Yuichi Mori, Shin-Ei Kudo, James E East...

https://pubmed.ncbi.nlm.nih.gov/32240683

ASGE Technology Committee systematic review and meta-analysis assessing the ASGE PIVI thresholds for adopting real-time endoscopic assessment of the histology of diminutive colorectal polyps.

ASGE Technology Committee, Barham K Abu Dayyeh, Nirav Thosani...

https://pubmed.ncbi.nlm.nih.gov/25597420